Hull and White and other authors in Mathematical Finance have introduced the so-called stochastic volatility models for taking into account some randomness which is specific to volatility (this randomness is due to exogenous arrivals of information). Later, Comte and Renault have proposed to replace the Brownian dynamic in these models by a fractional Brownian motion in order to make them more realistic. More recently, by using the notion of Generalized Quadratic Variations, Gloter and Hoffmann have constructed estimators of the parameters of Fractional stochastic volatility models. The goal of our talk is to introduce the multifractional Brownian motion and multifractional stochastic volatility models and to extend some results of Gloter and Hoffmann to these new models. At last, let us mention that the multifractional stochastic volatility models allow to take into account the fact that the local regularity of financial signals changes from one time to another.